DIAGNOSTIC EFFICIENCY IMPROVEMENT OF CORONARY HEART DISEASE IN ECHOCARDIOGRAPHY USING DYNAMIC RECOGNIZING ALGORITHM FROM COMPUTED NEURAL NETWORK

The segmental motion abnormality (SMA) is crucial for the diagnosis of coronary heart disease (CHD) in echocardiography however with poor accuracy and reproducibility based on reading experiences. We sought to use dynamic recognizing algorithm (DRA) from computed neural network (CNN) to improve CHD